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I need overall help with this project. From starting it to writing the analysis. Attached is the instructions and data to be used.
Different automobile manufacturers within and (in our case here) between countries have different price
characteristics, and these may in turn be affected by different variables. A separate data sheet, compiled
from a listing in the Pittsburgh Post-Gazette, has used car prices and their respective age and mileage
data for cars from Germany, Japan, (South) Korea and the United States for sale here in Pittsburgh.
The purpose of this project is to a) ascertain if and to what degree used car prices (dependent variable)
is explained by the corresponding independent variables, and b) arrive at a more general notion of
comparative ?value? when considering used cars.
1) Run a total of seven regressions:
(a) Two simple linear regression models, one each for used car price & age, and used car price &
miles, using the entire data set; i.e., all countries combined.
(b) One 2-variable model. Again, for the entire data set, run a multiple regression using both age
and miles. (Price is always your dependent variable.)
(b) Four 2-variable models. For each country (Germany, Japan, Korea and The US), run the same
multiple regressions using age and miles to explain variation in price.
2) Prepare a summary table in the following format (numbers are illustrations only):
Using your computer generated regression coefficients for each country, find the predicted
price for a used car in these two cases: 1) for a used car that is 3 years old with 20,000 miles;
and 2) for a used car that is 5 years old with 60,000 miles. Then, create a table that shows
these predicted prices, the dollar difference as a measure of predicted depreciation and the
percentage change in the depreciation interval period. Pct. Change = (newer model price ?
older model price) / older model price. For example (again, numbers are for illustration only):
Newer Model (3yr, 20K)
Older Model (5yr, 60K)
4) On a separate page summarize the results of your analysis.
a) For the entire sample taken together, in one paragraph (10 or 12-point font) discuss which is the
?best? regression model for explaining variation in used car pricing. Why? Consider all your indicators
(slopes, significance of t values, R2, in particular R2 adj., etc.) as well as multicollinearity issues in the
multiple regression model. Do you have any issues with the results? Why or why not? You may also
want to run a correlation analysis on the independent variables to test for multicollinearity.
b) For the four country regressions, in one paragraph briefly summarize the practical significance of
the regression results. You don?t need to say that ?R 2 for Germany is ---, and R2 for Japan is ---?. Your
table shows these. Rather, knowing what the statistical relationships are, what is the overall ?story? that
the results convey, along with any concerns you may have?
c) Using your table of predicted depreciation, discuss in one paragraph the notion of ?value? in
comparing used cars from the four countries. Specifically, how do the dollar differences in older vs. newer
predicted prices and the percentage changes in these predicted prices reflect how a country may be
evaluated (or judged?) on the quality of its automobile industry. Finally, it?s always nice to have an
introduction and a conclusion.
As is the case in these types of projects, items 3 and 4 are weighted more heavily. Take the
time to create and articulate good arguments while following the assignment parameters.
Submission: The discussion page (one page maximum), followed by your completed tables on the next
! Note: As I mentioned in class, please be advised that each of your written submissions must be unique.
In the past, more than a few written submissions have been, shall we say, similar. Indeed, some have
been virtually identical-- word-for-word copies of each other?s work, likely in noncompliance with the
School of Business Code of Ethics. This is not acceptable. Should I conclude that the submissions
received by two students are not sufficiently distinguishable, I will substantially and negatively adjust the
project scores for each student accordingly. This means that you must complete the project without
discussing or consulting with your classmates starting now and until after you submit your projects to me.
Finally, the act of submitting your project on the due date and time indicates you agree to abide by
whatever decision and actions I may take in this regard.
Paper#9209569 | Written in 27-Jul-2016Price : $19